We predict that in the future a large sum of money will be invested in recruiting highly trained and skilled personnel for data handling and downstream analysis. Various physicians, bioinformaticians, biologists, statisticians, geneticists, and scientific researchers will be required for genomic interpretation due to the ever increasing data.

Hence, for cost estimation, it is assumed that at least one bioinformatician (at $75,000), physician (at $110,000), biologist ($72,000), statistician ($70,000), geneticist ($90,000), and a technician ($30,000) will be required for interpretation of one genome. The number of technicians required in the future will decrease as processes are predicted to be automated. Also the bioinformatics software costs will plummet due to the decrease in computing costs as per Moore’s law.

Thus, the cost in 2011 for data handling and downstream processing is $285,000 per genome as compared to $517,000 per genome in 2017. These costs are calculated by tallying salaries of each person involved as well as the software costs.

These numbers would be seriously bad news for the future of genomic medicine, if they were even remotely connected with reality. Fortunately this is not the case. In fact this article (and other alarmist pieces on the “$1000 genome, $1M interpretation” theme) wildly overstate the economic challenges of genomic interpretation.